Method and apparatus for processing feedback in a wireless communication system

ABSTRACT

A method and apparatus for processing feedback implemented in a wireless transmit/receive unit (WTRU) comprises estimating a channel matrix. The effective channel is calculated and a precoding matrix is selected. Feedback bits are generated and transmitted.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.11/928,198, filed Oct. 30, 2007, which claims the benefit of U.S.Provisional Application No. 60/863,432, filed Oct. 30, 2006, U.S.Provisional Application No. 60/863,720, filed Oct. 31, 2006, and U.S.Provisional Application No. 60/870,503, filed Dec. 18, 2006, all ofwhich are incorporated herein by reference as if fully set forth herein,for all purposes.

FIELD OF INVENTION

The present invention is related to wireless communication systems.

BACKGROUND

Controlled feedback is used in a communication system to add layers ofcontrol to the system. The feedback systems currently used in wirelesscommunication systems are generally complex and consume valuableresources. One such system that employs feedback is an evolved universalterrestrial radio access (E-UTRA) multiple-in multiple-out (MIMO)system. Improving the efficiency of feedback and rank and linkadaptation to the closed-loop MIMO system for E-UTRA may therefore tendto improve MIMO link performance and system capacity, as well as reducesignaling overhead.

It would therefore be beneficial to provide a method and apparatus forprocessing feedback that could be employed, for example, in an E-UTRAMIMO system for both downlink (DL) and uplink (UL) communications.

SUMMARY

A method and apparatus for processing feedback implemented in a wirelesstransmit/receive unit (WTRU) is disclosed. The method includesestimating a channel matrix. The effective channel is calculated and aprecoding matrix is selected. Feedback bits are generated andtransmitted.

BRIEF DESCRIPTION OF THE DRAWINGS

A more detailed understanding of the invention may be had from thefollowing description, given by way of example and to be understood inconjunction with the accompanying drawings wherein:

FIG. 1 shows an example wireless communication system, including aplurality of wireless transmit/receive units (WTRUs) and a base station;

FIG. 2 is a flow diagram of a method of reset processing feedback;

FIG. 3 is a flow diagram of a method of fast adaptive processingfeedback;

FIG. 4 is a flow diagram of a method of slow adaptive processingfeedback;

FIG. 5 shows a functional block diagram of a WTRU and the base stationof FIG. 1;

FIG. 6 shows an alternative functional block diagram of a WTRU and thebase station of FIG. 1; and

FIG. 7 is a flow diagram of an additional method of processing feedback.

DETAILED DESCRIPTION

When referred to hereafter, the terminology “wireless transmit/receiveunit (WTRU)” includes but is not limited to a user equipment (UE), amobile station, a fixed or mobile subscriber unit, a pager, a cellulartelephone, a personal digital assistant (PDA), a computer, or any othertype of user device capable of operating in a wireless environment. Whenreferred to hereafter, the terminology “base station” includes but isnot limited to a Node-B, a site controller, an access point (AP), or anyother type of interfacing device capable of operating in a wirelessenvironment.

FIG. 1 shows an example wireless communication system 100, including aplurality of WTRUs 110 and a base station 120. As shown in FIG. 1, theWTRUs 110 are in communication with the base station 120. Although twoWTRUs 110, and one base station 120 are shown in FIG. 1, it should benoted that any combination of wireless and wired devices may be includedin the wireless communication system 100.

FIG. 2 is a flow diagram of a method 200 of reset processing feedback.In reset processing, non-differential feedback is utilized. In step 210of method 200, the channel matrix is estimated. Once the channel matrixis estimated, the effective channel is calculated (step 220). In oneexample, the effective channel is calculated as a multiplication of thechannel estimate and the precoding matrix, such as H_eff=H_est×T, whereH_est is the channel estimate and T is the precoding matrix. Theeffective channel is calculated for all possible candidate precodingmatrices, sub-matrices, or vectors. A metric is computed using theeffective channel that may include signal to interference plus noiseratio (SINR), throughput, block or frame error rate, channel capacity,and the like.

A precoding matrix or vector is then selected or calculated (step 230).The best matrix, submatrix or vector should be selected based on channelquality, SINR, throughput, block error ration (BLER), frame error ratio(FER) or other similar measures or combinations. For example the SINRfor a linear minimum mean squared error (LMMSE) receiver can be computedand the precoding matrix that has the largest SINR may be selected.Other methods based on effective channels and their corresponding CQImeasurements can also be used to select the precoding matrix or vector.In the case of calculating the matrix or vector, the channel matrixestimate is used as a base and the precoding matrix is computed byperforming, for example, a singular value decomposition (SVD) oreigen-value decomposition (EVD) on the channel matrix estimate, and thenquantized using a predetermined codebook.

One way for selecting the precoding matrix is that the channel responsesH are estimated and a singular value decomposition (SVD) is performed onthe estimated Hs to obtain a precoding matrix V. For N streams of MIMOtransmission, where 1≦N≦N_(t), A is a sub-matrix of V that representsthe N stream precoding of data. Furthermore B_(i) is the possiblecombinations of N column vectors of a matrix F. All the possiblecombinations of column vectors of F, (i.e., all the possible B_(i)), maybe searched and the one selected which maximizes the sum of norm of theinner product or correlation of A and B_(i) in the search in accordancewith the following equation:

$\begin{matrix}{T = {\max\limits_{B_{i}}{\sum\limits_{j = 1}^{N}\;{{\langle {{A( {:{,j}} )}^{*},{B_{i}( {:{,j}} )}} \rangle }.}}}} & {{Equation}\mspace{14mu}(1)}\end{matrix}$

A discrete Fourier transform (DFT) matrix may be utilized for MIMOprecoding, and a set of precoding matrices can be constructed using aDFT matrix multiplied with different phase shifts. The set of DFTmatrices can be used as a MIMO precoding codebook based on whether theprecoding matrix is either selected or quantized.

A DFT matrix can be represented by

${w_{m,n} = {\mathbb{e}}^{{j2\pi}\; m\frac{n}{N}}},$where m=0, 1, 2, . . . , N−1 and n=0, 1, 2, . . . , N−1. A two-by-two(2×2) DFT matrix may be expressed as:

$\begin{matrix}{F_{2 \times 2} = {\begin{bmatrix}1 & 1 \\1 & {- 1}\end{bmatrix}.}} & {{Equation}\mspace{14mu}(2)}\end{matrix}$

A four-by-four (4×4) DFT matrix may be expressed as:

$\begin{matrix}{F_{4 \times 4} = {\begin{bmatrix}1 & 1 & 1 & 1 \\1 & j & {- 1} & {- j} \\1 & {- 1} & 1 & {- 1} \\1 & {- j} & {- 1} & j\end{bmatrix}.}} & {{Equation}\mspace{14mu}(3)}\end{matrix}$

A set of precoding matrices can be generated using different phaseshifts in accordance with the following equation:

$\begin{matrix}{{w_{m,n} = {\mathbb{e}}^{{j2\pi}\;{{m{({n + \frac{l}{L}})}}/N}}},} & {{Equation}\mspace{14mu}(4)}\end{matrix}$

where m=1, 2, . . . , N−1, n=0, 1, 2, . . . , N−1 and l=0, 1, 2, . . . ,L−1. To generate a set of eight 4×4 matrices, L=8 and N=4 are used,where N and L are design parameters to generate L DFT matrices of sizeN×N. Accordingly, a set of 4×4 precoding matrices may be constructed asfollows:

$\begin{matrix}{{{F_{{4 \times 4},0} = \begin{bmatrix}1 & 1 & 1 & 1 \\1 & {\mathbb{e}}^{j\frac{1}{2}\pi} & {\mathbb{e}}^{j\pi} & {\mathbb{e}}^{{- j}\frac{1}{2}\pi} \\1 & {\mathbb{e}}^{j\pi} & {\mathbb{e}}^{j2\pi} & {\mathbb{e}}^{j\pi} \\1 & {\mathbb{e}}^{{- j}\frac{1}{2}\pi} & {\mathbb{e}}^{j\pi} & {\mathbb{e}}^{j\frac{1}{2}\pi}\end{bmatrix}};}{{F_{{4 \times 4},1} = \begin{bmatrix}1 & 1 & 1 & 1 \\{\mathbb{e}}^{j\frac{1}{16}\pi} & {\mathbb{e}}^{j\frac{9}{16}\pi} & {\mathbb{e}}^{{- j}\frac{15}{16}\pi} & {\mathbb{e}}^{{- j}\frac{7}{16}\pi} \\{\mathbb{e}}^{j\frac{1}{8}\pi} & {\mathbb{e}}^{{- j}\frac{7}{8}\pi} & {\mathbb{e}}^{j\frac{1}{8}\pi} & {\mathbb{e}}^{{- j}\frac{7}{8}\pi} \\{\mathbb{e}}^{j\frac{3}{16}\pi} & {\mathbb{e}}^{{- j}\frac{5}{16}\pi} & {\mathbb{e}}^{{- j}\frac{13}{16}\pi} & {\mathbb{e}}^{j\frac{11}{16}\pi}\end{bmatrix}};}{{F_{{4 \times 4},2} = \begin{bmatrix}1 & 1 & 1 & 1 \\{\mathbb{e}}^{j\frac{1}{8}\pi} & {\mathbb{e}}^{j\frac{5}{8}\pi} & {\mathbb{e}}^{{- j}\frac{7}{8}\pi} & {\mathbb{e}}^{{- j}\frac{3}{8}\pi} \\{\mathbb{e}}^{j\frac{1}{4}\pi} & {\mathbb{e}}^{{- j}\frac{3}{4}\pi} & {\mathbb{e}}^{j\frac{1}{4}\pi} & {\mathbb{e}}^{{- j}\frac{3}{4}\pi} \\{\mathbb{e}}^{j\frac{3}{8}\pi} & {\mathbb{e}}^{{- j}\frac{1}{8}\pi} & {\mathbb{e}}^{{- j}\frac{5}{8}\pi} & {\mathbb{e}}^{j\frac{7}{8}\pi}\end{bmatrix}};}{{F_{{4 \times 4},3} = \begin{bmatrix}1 & 1 & 1 & 1 \\{\mathbb{e}}^{j\frac{3}{16}\pi} & {\mathbb{e}}^{j\frac{11}{16}\pi} & {\mathbb{e}}^{{- j}\frac{13}{16}\pi} & {\mathbb{e}}^{{- j}\frac{5}{16}\pi} \\{\mathbb{e}}^{j\frac{3}{8}\pi} & {\mathbb{e}}^{{- j}\frac{5}{8}\pi} & {\mathbb{e}}^{j\frac{3}{8}\pi} & {\mathbb{e}}^{{- j}\frac{5}{8}\pi} \\{\mathbb{e}}^{j\frac{9}{16}\pi} & {\mathbb{e}}^{j\frac{1}{16}\pi} & {\mathbb{e}}^{{- j}\frac{7}{16}\pi} & {\mathbb{e}}^{{- j}\frac{15}{16}\pi}\end{bmatrix}};}{{F_{{4 \times 4},4} = \begin{bmatrix}1 & 1 & 1 & 1 \\{\mathbb{e}}^{j\frac{1}{4}\pi} & {\mathbb{e}}^{j\frac{3}{4}\pi} & {\mathbb{e}}^{{- j}\frac{3}{4}\pi} & {\mathbb{e}}^{{- j}\frac{1}{4}\pi} \\{\mathbb{e}}^{j\frac{1}{2}\pi} & {\mathbb{e}}^{{- j}\frac{1}{2}\pi} & {\mathbb{e}}^{j\frac{1}{2}\pi} & {\mathbb{e}}^{{- j}\frac{1}{2}\pi} \\{\mathbb{e}}^{j\frac{3}{4}\pi} & {\mathbb{e}}^{j\frac{1}{4}\pi} & {\mathbb{e}}^{{- j}\frac{1}{4}\pi} & {\mathbb{e}}^{j\frac{5}{4}\pi}\end{bmatrix}};}{{F_{{4 \times 4},5} = \begin{bmatrix}1 & 1 & 1 & 1 \\{\mathbb{e}}^{j\frac{5}{16}\pi} & {\mathbb{e}}^{j\frac{13}{16}\pi} & {\mathbb{e}}^{{- j}\frac{11}{16}\pi} & {\mathbb{e}}^{{- j}\frac{3}{16}\pi} \\{\mathbb{e}}^{j\frac{5}{8}\pi} & {\mathbb{e}}^{{- j}\frac{3}{8}\pi} & {\mathbb{e}}^{j\frac{5}{8}\pi} & {\mathbb{e}}^{{- j}\frac{3}{8}\pi} \\{\mathbb{e}}^{j\frac{15}{16}\pi} & {\mathbb{e}}^{j\frac{7}{16}\pi} & {\mathbb{e}}^{{- j}\frac{1}{16}\pi} & {\mathbb{e}}^{{- j}\frac{9}{16}\pi}\end{bmatrix}};}{{F_{{4 \times 4},6} = \begin{bmatrix}1 & 1 & 1 & 1 \\{\mathbb{e}}^{j\frac{3}{8}\pi} & {\mathbb{e}}^{j\frac{7}{8}\pi} & {\mathbb{e}}^{{- j}\frac{5}{8}\pi} & {\mathbb{e}}^{{- j}\frac{1}{8}\pi} \\{\mathbb{e}}^{j\frac{3}{4}\pi} & {\mathbb{e}}^{j\frac{1}{4}\pi} & {\mathbb{e}}^{j\frac{3}{4}\pi} & {\mathbb{e}}^{j\frac{1}{4}\pi} \\{\mathbb{e}}^{j\frac{9}{8}\pi} & {\mathbb{e}}^{j\frac{5}{8}\pi} & {\mathbb{e}}^{j\frac{1}{8}\pi} & {\mathbb{e}}^{{- j}\frac{3}{8}\pi}\end{bmatrix}};}{F_{{4 \times 4},7} = {\begin{bmatrix}1 & 1 & 1 & 1 \\{\mathbb{e}}^{j\frac{7}{16}\pi} & {\mathbb{e}}^{j\frac{15}{16}\pi} & {\mathbb{e}}^{{- j}\frac{9}{16}\pi} & {\mathbb{e}}^{{- j}\frac{1}{16}\pi} \\{\mathbb{e}}^{j\frac{7}{8}\pi} & {\mathbb{e}}^{{- j}\frac{1}{8}\pi} & {\mathbb{e}}^{j\frac{7}{8}\pi} & {\mathbb{e}}^{{- j}\frac{1}{8}\pi} \\{\mathbb{e}}^{j\frac{11}{16}\pi} & {\mathbb{e}}^{j\frac{13}{16}\pi} & {\mathbb{e}}^{j\frac{5}{16}\pi} & {\mathbb{e}}^{{- j}\frac{3}{16}\pi}\end{bmatrix}.}}} & {{Equation}\mspace{14mu}(5)}\end{matrix}$

A set of 2×2 matrices may be generated and constructed in a similarmanner.

In step 240, feedback bits are generated and transmitted. The feedbackbits include the corresponding codeword index. In the case of 4×4 MIMOmatrix, and for full rank, (i.e., the rank equals four (4)), an indexassociated with one of the matrices identified in equation (5) may beused as the feedback input. For a rank less than four (4), an indexassociated with one of the column subsets of the matrices in equation(5) may be used as the feedback input. For the case where the rankequals one, an index associated with one of the column vectors of thematrices may be used as the feedback input.

An additional feedback mechanism utilizes adaptive processing. Ingeneral, adaptive processing is either “fast adaptive” or “slowadaptive” depending on degree of accuracy of updating with respect tothe desired precoding matrix or convergence rate.

FIG. 3 is a flow diagram of a method 300 of fast adaptive processingfeedback. Fast adaptive processing feedback is a fast tracking methodand can be used as a stand-alone feedback or as a feedback which is inconjunction with the full precoding matrix feedback depicted in method200 of FIG. 2. In step 310, the differential precoding matrix or deltamatrix is computed. Then the differential precoding matrix or deltamatrix is quantized (step 320).

Feedback bits are generated and transmitted (step 330), where thefeedback bits correspond to a codeword index of a differential codebook.The more feedback bits that are used, the faster the precoding matrix isupdated using the feedback bits, which represent the differentialprecoding matrix. Accordingly, faster adaptive processing may beachieved.

FIG. 4 is a flow diagram of a method 400 of slow adaptive processingfeedback. Slow adaptive processing feedback is a slow tracking methodand can be used as a stand-alone feedback or as a feedback which is inconjunction with the full precoding matrix feedback (reset) depicted inmethod 200 of FIG. 2. Slow adaptive processing feedback can also be usedin conjunction with the differential precoding matrix feedback depictedin method 300 of FIG. 3, or a combination of the methods 200 and 300 ofFIGS. 2 and 3, respectively.

In step 410, a single binary sign bit is computed, and the single binarysign bit is then transmitted (step 420), for example from a receiverdevice to a transmitter device. The single binary sign bit, b[n], may becomputed using a measurement of the effective channel in accordance withthe following equation:b[n]=sign(q[n]).  Equation (6)

The measure q[n] is an effective channel measurement for the preferreddirection that maximizes the received power. If Ω₁[n] and Ω₀[n] aredenoted to be Ω₁[n]={tilde over (T)}[n]exp(F[n])Y and Ω₀[n]={tilde over(T)}[n]exp(−F[n])Y, respectively, then q[n] may be expressed as:q[n]=∥H[n+1]Ω₁ [n]∥ _(F) ² −∥H[n+1]Ω₀ [n]∥ _(F) ².  Equation (7)

If the direction of received power maximization is toward Ω₁[n], thenb[n]=1 is transmitted (step 420). Otherwise, the direction of receivedpower maximization is toward Ω₀[n], and the feedback b[n]=−1 istransmitted (step 420).

The index to the best precoding matrix or vector is selected and fedback, (i.e., transmitted). The precoding matrix is updated during theperiod between resets or between full precoding matrix updates for thefollowing feedback interval by the single binary bit for slow adaptiveprocessing, or slow tracking of the best selected precoding matrix whichis selected at reset period.

For example, letting Nt denote the number of transmit antennas and Nsdenote the number of transmitted data streams, the precoding matrix thatis fed back is T[n] for a feedback instance n. The precoding matrixT[n], then, is updated by the single binary bit b[n] that is fed backfrom a receiver at feedback instance n+1. The precoding matrix isupdated from T[n] to T[n+1] using feedback bit b[n].

Grassmann manifold or Grassmann line packing can be used to define thebeamforming space. A signal flow along the curve of the shortest lengthin Grassmann manifold G_(Nt,Ns) and can be expressed as:Q(t)=Q(0)exp(tX)Y,  Equation (8)where Q(0) and Q(t) are the points in Grassmann manifold space at time 0and t respectively. X is a skew-symmetric matrix and is restricted to beof the form:

$\begin{matrix}{X = {\begin{bmatrix}0 & {- Z^{H}} \\Z & 0\end{bmatrix}.}} & {{Equation}\mspace{14mu}(9)}\end{matrix}$

The matrix Y may be expressed by:

$\begin{matrix}{Y = {\begin{bmatrix}I_{N_{s}} \\0_{{({N_{t} - N_{s}})} \times N_{s}}\end{bmatrix}.}} & {{Equation}\mspace{14mu}(10)}\end{matrix}$

The precoding matrix and its update may then be defined in accordancewith the following equation:

$\begin{matrix}{{{T\lbrack {n + 1} \rbrack} = {{\overset{\sim}{T}\lbrack n\rbrack}{\exp( {{b\lbrack n\rbrack}{F\lbrack n\rbrack}} )}Y}},{where}} & {{Equation}\mspace{14mu}(11)} \\{{{F\lbrack n\rbrack} = \begin{bmatrix}0 & {- {G^{H}\lbrack n\rbrack}} \\{G\lbrack n\rbrack} & 0\end{bmatrix}},} & {{Equation}\mspace{14mu}(12)}\end{matrix}$

and has dimension Nt by Nt. {tilde over (T)}[n]=[T[n] E[n]] is a unitarymatrix of dimension Nt by Nt and E[n] is the orthogonal complement ofT[n]. Matrix Y has dimension Nt by Ns. Matrix G[n] is a random matrixand has dimension Nt−Ns by Ns. Matrix G[n] is used to approximate matrixZ and is generated with a certain distribution, of which one example isuniform distribution. Another example is independent and identicalcomplex Gaussian distribution with zero mean and variance) β². That is,each entry of G[n] is independently and identically distributed, (e.g.,CN(0,β²)). However, other proper distributions for G[n] may also beconsidered and used. The exponential term exp(b[n]F[n])Y represents thesignal flow from the current to the next precoding matrix along thecurve of the shortest length in the beamforming space. The single binarybit b [n] determines one of the two opposite directions of the signalflow determined by F[n] along the curve of the shortest length in thebeamforming space when the precoding matrix is updated.

In order to obtain the same update for the precoding matrix, the matrixG[n] should be known to both a transmitter and receiver. This can bedone by synchronously generating G[n] by pseudo random number generatorsat the transmitter and the receiver at the time when communicationbetween the transmitter and receiver starts. However, signaling may alsobe utilized to communicate the information about matrix G between thetransmitter and receiver.

The parameter β² in matrix G is a step size of the precoding matrixupdate and can be static, semi-static or dynamic. For optimumperformance the parameter β² should be adaptively adjusted according toDoppler shift, with the value of β² increasing as Doppler frequencyincreases, and vice versa.

The feedback rate, or feedback interval, depends on the rate of channelvariation or vehicle speed. The optimum feedback rate or interval may bedetermined using simulations. A fixed feedback rate or interval can beused to compromise between different vehicle speeds or channelvariation. A feedback rate or interval can also be configured orreconfigured to meet certain performance requirements. Additionally, ifinformation about vehicle speed or Doppler shift are available, thatinformation may be used to configure or reconfigure the feedback rate orinterval. The step size of the precoding matrix update can also bedetermined or optimized according to different rates of channelvariation.

T[n+1], given T[n] and G[n], may be computed using compact singular (CS)decomposition and the like. For example, the matrix G[n] may bedecomposed using singular value decomposition (SVD) in accordance withthe following equation:G[n]=V ₂ ΘV ₁ ^(H).  Equation (13)

The matrix Θ is a diagonal matrix such that:Θ=diag(θ₁,θ₂, . . . ,θ_(N) _(s) ),  Equation (14)

The variables θ_(i), where i=1, 2, . . . , N, are the principal anglesbetween the subspaces T[n] and T[n+1]. If the feedback bit b[n] is −1,−G[n] may be decomposed instead.

The values of sin(θ_(i)) and cos(θ_(i)) for i=1, 2, . . . , N_(s), arecomputed and diagonal matrices C and S are constructed such that:C=diag(cos θ₁, cos θ₂, . . . , cos θ_(N) _(s) ),  Equation (15)andS=diag(sin θ₁, sin θ₂, . . . , sin θ_(N) _(s) ).  Equation (16)

The matrix T[n+1] may be computed in accordance with the followingequation:

$\begin{matrix}{{T\lbrack {n + 1} \rbrack} = {{{\overset{\sim}{T}\lbrack n\rbrack}\begin{bmatrix}{V_{1}C} \\{V_{2}S}\end{bmatrix}}.}} & {{Equation}\mspace{14mu}(17)}\end{matrix}$

Reset processing or non-differential feedback may be used initially andperiodically every N transmission time intervals (TTIs) to reset theerror arising from differential and binary feedback. In addition, resetor non-differential feedback may be used aperiodically. The fastadaptive processing or differential feedback may be used for “X” TTIsfollowing the initialization, reset or non-differential feedback. Theslow adaptive processing or binary feedback may be used between the timewhen a fast adaptive feedback period ends and the time when the reset ornon-differential feedback begins.

FIG. 5 shows a functional block diagram 500 of a WTRU 110 and a basestation 120′ of FIG. 1. The WTRU 110 and base station 120′ of FIG. 5 areconfigured to perform any combination of the methods 200, 300, and 400described in FIGS. 2, 3, and 4, and are in wireless communication withone another. The methods 200, 300, and 400 in FIGS. 2, 3, and 4 can beused in different time or different feedback intervals between the basestation 120′ and the WTRU 110. In the example shown in FIG. 5, the basestation 120′ may be considered as a transmitter, or transmitting device,while the WTRU 110 is a receiver, or receiving device.

In addition to other components that may be included in a WTRU, (e.g., atransmitter, a receiver, and the like), the WTRU 110 of FIG. 5 includesa channel estimator 115 and a feedback bit generator 116 incommunication with the channel estimator 115. In addition, the WTRU 110includes a first antenna 117 and a second antenna 118. As depicted inFIG. 5, the first antenna 117 is in communication with the channelestimator 115 and may receive and forward wireless communications fromthe base station 120 to the channel estimator 115. The second antenna118 is in communication with the feedback bit generator 116 and mayreceive a signal from the feedback bit generator 116 and transmit it tothe base station 120′. It should be noted however, that any number andconfiguration of antennas may be included in the WTRU 110. For example,the first antenna 117 may be in communication with the feedback bitgenerator 116 and the second antenna 118 may be in communication withthe channel estimator 115. The channel estimator 115 is configured toperform the channel estimation functions described in methods 200, 300,and 400 of FIGS. 2, 3, and 4, respectively. The feedback bit generator116 is configured to generate the feedback to be transmitted back to thebase station 120′ in accordance with the methods 200, 300, and 400 ofFIGS. 2, 3, and 4, respectively, or any combination of methods 200, 300,and 400.

A generate matrix G functional block 531 is in communication with thefeedback bit generator block 116 of the WTRU 110, and a doppleradjustment block 541 is in communication with the generate matrix Gfunctional block 531. The generate matrix G functional block 531 anddoppler adjustment block 541 are configured to perform the relatedfunctions described in methods 200, 300, and 400, of FIGS. 2, 3, and 4,respectively.

In addition to other components that may be included in a base station,(e.g., a transmitter, a receiver, and the like), the base station 120′includes a precoding block 121, a precoding matrix update block 122, arank adapter 123, and a multiplexer (MUX) 124. The precoding block 121is in communication with the precoding matrix update block 122, the rankadapter 123 and the MUX 124. In addition, a first antenna 125 is incommunication with the MUX 124 and may receive a signal from the MUX 124to facilitate wireless communication to the WTRU 110. A second antenna126 is in communication with the precoding matrix update block 122, andmay facilitate the reception of wireless communications received fromthe WTRU 110. It should be noted again that either antenna, 125 or 126,may be in communication with any of the components. The precoding block121 is further configured to receive a data signal, and the MUX 124 isconfigured to also receive a pilot signal. In addition, the precodingblock 121, precoding matrix update block 122, and the rank adapter 123are configured to perform the related functions described in methods200, 300, and 400, of FIGS. 2, 3, and 4, respectively, or anycombination of methods 200, 300, and 400.

A generate matrix G functional block 530 is in communication with theprecoding matrix update block 122 of the base station 120′, and adoppler adjustment block 540 is in communication with the generatematrix G functional block 530. The generate matrix G functional block530 and doppler adjustment block 540 are configured to perform therelated functions described in methods 200, 300, and 400, of FIGS. 2, 3,and 4, respectively.

FIG. 6 shows an alternative functional block diagram 600 of a WTRU 110and a base station 120″ of FIG. 1. The WTRU 110 and base station 120″ ofFIG. 6 are configured to perform any combination of the methods 200,300, and 400 described in FIGS. 2, 3, and 4, and are in wirelesscommunication with one another. The WTRU 110 shown in FIG. 6 issubstantially similar to the WTRU 110 described above in FIG. 5. In theexample shown in FIG. 6, the base station 120″ may be considered as atransmitter, or transmitting device, while the WTRU 110 is a receiver,or receiving device.

A generate matrix G functional block 631 is in communication with thefeedback bit generator block 116 of the WTRU 110. A doppler adjustmentblock 641 is in communication with the generate matrix G functionalblock 631. The generate matrix G functional block 631 and doppleradjustment block 641 are configured to perform the related functionsdescribed in methods 200, 300, and 400, of FIGS. 2, 3, and 4,respectively.

In addition to other components that may be included in a base station,(e.g., a transmitter, a receiver, and the like), the base station 120″includes a precoding block 621, a precoding matrix update block 622, alink adapter 623, and a multiplexer (MUX) 624. The precoding block 621is in communication with the precoding matrix update block 622, the linkadapter 623 and the MUX 624. In addition, a first antenna 625 is incommunication with the MUX 624 and may receive a signal from the MUX 624to facilitate wireless communication to the WTRU 110. A second antenna626 is in communication with the precoding matrix update block 622, andmay facilitate the reception of wireless communications received fromthe WTRU 110. The precoding block 621 is further configured to receive adata signal, and the MUX 624 is configured to also receive a pilotsignal. In addition, the precoding block 621, precoding matrix updateblock 622, and the link adapter 623 are configured to perform therelated functions described in methods 200, 300, and 400, of FIGS. 2, 3,and 4, respectively.

A generate matrix G functional block 630 is in communication with theprecoding matrix update block 622 of the base station 120″. A doppleradjustment block 640 is in communication with the generate matrix Gfunctional block 630. The generate matrix G functional block 630 anddoppler adjustment block 640 are configured to perform the relatedfunctions described in methods 200, 300, and 400, of FIGS. 2, 3, and 4,respectively.

FIG. 7 is a flow diagram of an additional method 700 of processingfeedback. In step 710, the channel matrix His measured. A sign bit isthen computed (step 720), based on the direction of the geodesic thatmaximizes received power. The sign bit is then transmitted (step 730),for example from a receiver to a transmitter, and the precoding matrixis updated (step 740) by the transmitter using the sign bit so that thenew precoding matrix approaches the direction of maximizing receiverpower for the next precoding operation.

Although features and elements are described above in particularcombinations, each feature or element can be used alone without theother features and elements or in various combinations with or withoutother features and elements. The methods or flow charts provided hereinmay be implemented in a computer program, software, or firmware tangiblyembodied in a computer-readable storage medium for execution by ageneral purpose computer or a processor. Examples of computer-readablestorage mediums include a read only memory (ROM), a random access memory(RAM), a register, cache memory, semiconductor memory devices, magneticmedia such as internal hard disks and removable disks, magneto-opticalmedia, and optical media such as CD-ROM disks, and digital versatiledisks (DVDs).

Suitable processors include, by way of example, a general purposeprocessor, a special purpose processor, a conventional processor, adigital signal processor (DSP), a plurality of microprocessors, one ormore microprocessors in association with a DSP core, a controller, amicrocontroller, Application Specific Integrated Circuits (ASICs), FieldProgrammable Gate Arrays (FPGAs) circuits, any other type of integratedcircuit (IC), and/or a state machine.

A processor in association with software may be used to implement aradio frequency transceiver for use in a wireless transmit receive unit(WTRU), user equipment (UE), terminal, base station, radio networkcontroller (RNC), or any host computer. The WTRU may be used inconjunction with modules, implemented in hardware and/or software, suchas a camera, a video camera module, a videophone, a speakerphone, avibration device, a speaker, a microphone, a television transceiver, ahands free headset, a keyboard, a Bluetooth® module, a frequencymodulated (FM) radio unit, a liquid crystal display (LCD) display unit,an organic light-emitting diode (OLED) display unit, a digital musicplayer, a media player, a video game player module, an Internet browser,and/or any wireless local area network (WLAN) module.

What is claimed is:
 1. A method for processing feedback bits implementedin a wireless transmit/receive unit (WTRU), comprising: estimating achannel matrix by the wireless WTRU; calculating an effective channel;selecting a precoding matrix from a set of precoding matrices; computinga differential precoding matrix or delta matrix; quantizing thedifferential precoding matrix or delta matrix; generating the feedbackbits by the WTRU; and transmitting the feedback bits from the WTRU,wherein the set of precoding matrices is constructed using a DiscreteFourier Transform (DFT) matrix multiplied with different phase shifts.2. The method of claim 1 wherein selecting the precoding matrix includesselecting the precoding matrix based upon a metric, wherein the metricincludes any one of the following: signal to interference noise ratio(SINR), throughput, block error rate (BER), frame error rate, andchannel capacity.
 3. The method of claim 1 wherein the effective channelis a multiplication of the channel estimate with precoding matrices. 4.The method of claim 1 wherein selecting the precoding matrix includescalculating the precoding matrix from the channel matrix estimate. 5.The method of claim 4 wherein selecting the precoding matrix furthercomprises: quantizing the precoding matrix using a predeterminedcodebook.
 6. The method of claim 1 wherein the feedback bits include acodeword index.
 7. The method of claim 1, further comprising: updatingthe precoding matrix.
 8. A method for processing feedback bitsimplemented in a wireless transmit/receive unit (WTRU), comprising:constructing a set of precoding matrices using a Discrete FourierTransform (DFT) matrix multiplied with different phase shifts; selectinga precoding matrix from the set of precoding matrices by the by thewireless WTRU; computing a differential precoding matrix or deltamatrix; quantizing the differential precoding matrix or delta matrix;generating the feedback bits by the WTRU; and transmitting the feedbackbits from the WTRU.
 9. The method of claim 8 wherein the feedback bitsinclude a codeword index.
 10. The method of claim 8, further comprising:updating the precoding matrix.
 11. A wireless transmit/receive unit(WTRU), comprising: a channel estimator configured to receive a signaland estimate a channel; and a feedback bit generator in communicationwith the channel estimator, the feedback bit generator configured todetermine a precoding matrix from a set of precoding matrices, generatea differential feedback bit and transmit the differential feedback bit,wherein the set of precoding matrices is constructed using a DiscreteFourier Transform (DFT) matrix multiplied with different phase shifts.12. The WTRU of claim 11 wherein the feedback bit generator is furtherconfigured to generate a binary feedback bit.
 13. The WTRU of claim 11wherein the feedback bit generator is configured to generate anon-differential feedback bit.
 14. The WTRU of claim 11 wherein theprecoding matrix is determined based upon at least one of: a signal tointerference noise ratio (SINR), a throughput, a block error rate (BER),a frame error rate, or a channel capacity.
 15. The WTRU of claim 11,wherein the feedback bit generator is further configured to determine afeedback rate based at least in part on a Doppler adjustment.
 16. Awireless transmit/receive unit (WTRU), comprising: a channel estimatorconfigured to receive a signal and estimate a channel; and a feedbackbit generator in communication with the channel estimator, the feedbackbit generator configured to determine a precoding matrix from a set ofprecoding matrices, generate a binary feedback bit and transmit a binaryfeedback bit, wherein the set of precoding matrices is constructed usinga Discrete Fourier Transform (DFT) matrix multiplied with differentphase shifts.
 17. The WTRU of claim 16 wherein the feedback bitgenerator is configured to generate a non-differential feedback bit. 18.The WTRU of claim 16 wherein the feedback bit generator is configured togenerate a differential feedback bit.
 19. The WTRU of claim 16 whereinthe precoding matrix is further determined based upon at least one of: asignal to interference noise ratio (SINR), a throughput, a block errorrate (BER), a frame error rate, or a channel capacity.
 20. The WTRU ofclaim 16, wherein the feedback bit generator is further configured todetermine a feedback rate based at least in part on a Doppleradjustment.